The overall goal of this proposal is to develop techniques for quantitative analysis of the biodistribution radiolabeled antibodies in vivo and in vitro. I propose to perform methods of quantitative gamma camera imaging of human phantoms to analyze the errors in estimating the radioactive content of normal organs and radiolabeled tumors. At the tissue level, I propose to quantitatively analyze the microscopic distribution of infused radiolabeled antibodies by computerized image digitization of immunoperoxidase stained and microscopic autoradiographed sections of patient tumors and animal model tumor tissues. These techniques will be used to analyze radiolabeled antibody distribution in cancer patients for the purpose of calculating accurate dosimetry estimates for their radioimmunotherapy doses in our ongoing protocols at the University of Washington. Currently, uncertainty in dosimetric estimates is the limiting factor in selecting the dose (both in milligrams of antibody and in mCi of radioisotope) to be administered for a particular radioimmunotherapy patient. Nuclear gamma camera methods of quantitative imaging involve acquiring opposing views of an organ, correcting the geometric mean of counts obtained in that organ for body attenuation and applying a camera calibration factor. This method, while reasonably accurate, has unknown reliability for small sources such as tumors with low radioactive content. The accuracy of this method certainly influences calculations of radioiodine dose to normal organs and tumors. Information obtained from examination of tumor tissues is currently qualitative and plays a minor role in the decision making process for planning radioimmunotherapy. Information obtained by quantitative examination of antibody distribution at the microscopic level will allow more effective estimates of the labeled antibody dosimetry in patient tumors at the cellular level. This study, in conjunction with improved gamma camera imaging will provide more accurate data for planning individualized dosimetric estimates for our radioimmunotherapy patients.